We follow the same experimental settings as in [1]}, and compare the performance of a bilinear network based on the proposed LR-TABL layer to that of a bilinear network based on the TABL layer. That is, we use as input the raw Limit Order Book data having ten levels of limit orders and we use the ten most recent instances to form the time-series, i.e. input to the networks is \(\mathbf {X} \in \mathbb {R}^{40 \times 10}\) . We introduce this time-series to the two networks and we predict the direction in the mid-price ('up', 'stationary', 'down') at prediction horizon of \(H = 10\) . To have better understanding of performance of the proposed approach, we use the same network structures used in [1]}, which are the following:
